Guru Singh, Founder and CEO of Scispot joins Dr. Yin He, Principal Business Development, Healthcare and Life Sciences Startups from AWS on the AWS Health Innovation Podcast. Scispot helps over 100 BioTechs collect, clean, and activate their data. Scispot builds connectors to aggregate disconnected data into knowledge graphs, preparing it for analysis and AI, thus supercharging R&D. A decade ago, BioTech work was 90% wet lab and 10% dry lab, but it is closer to 50/50 today, creating friction for scientists who have to combine, annotate and analyze data manually. Scispot aims to fully automate these workflows so scientists can focus purely on experimentation. We’ll cover Guru’s vision for in-silico models replacing animal testing, the monumental opportunity to reduce drug development timelines from a decade to months, and many other topics.

Digital Transformation - Scispot provides the data infrastructure to help biotech companies leverage AI/ML and transition from being 90% wet lab to 50/50 wet lab and dry lab. Eventually the industry is likely to evolve to the point where wet lab work and animal models are replaced with computational modeling and experimentation.

Knowledge Graphs - Scispot builds connectors to aggregate siloed data then applies entity recognition to create knowledge graphs, harmonizing data into easily computable formats. This enables building AI models and recommendations.

Templatized Workflows - By standardizing and templatizing workflows for common experiments and processes, Scispot aims to let scientists focus on science rather than infrastructure.

Data Strategy - Scispot emphasizes starting with a data strategy and capturing all data from the beginning, so it can be leveraged for future AI initiatives. Unique, proprietary data is a competitive advantage.

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